Functional connectivity and effective connectivity of the human brain, representing statistical
dependence and directed information flow between cortical regions, significantly contribute …

This study aimed to develop a time–frequency method for measuring directional interactions
over time and frequency from scalp-recorded electroencephalographic (EEG) signals in a …

A Time-Varying Causality Formalism Based on the Liang–Kleeman Information Flow for
Analyzing Directed Interactions in Nonstationary Climate Systems in: Journal of Climate …

Human brain function depends on directed interactions between multiple areas that evolve
in the subsecond range. Time-varying multivariate autoregressive (tvMVAR) modeling has …

The multivariate autoregressive (MVAR) model is widely used in describing the dynamics of
nonlinear systems, in which the estimates of model parameters and underlying states can be …

Conventional neuroimaging analyses have ascribed function to particular brain regions,
exploiting the power of the subtraction technique in fMRI and event-related potential …

Abstract Background Frequency domain Granger causality measures have been proposed
and widely applied in analyzing rhythmic neurophysiological and biomedical signals. Almost …

Abstract Nowadays Brain Computer Interface (BCI) is one of the most important fields in
neuroscience in which machine works are controlled with the human brain. Motor imagery …

Objective. Electroencephalogram (EEG)-based motor imagery (MI) brain-computer interface
offers a promising way to improve the efficiency of motor rehabilitation and motor skill …

Abstract" The mind is the music that neural networks play." This quote from computational
neurobiologist TJ Sejnowski underscores a growing scientific consensus that studying the …